Manager, Applied AI Engineering, Life Sciences

Responsibilities

• Build and lead the team: hire, coach, and develop a team of Applied AI Engineers dedicated to strategic life sciences partners, setting a high technical bar and helping each engineer grow.
• Own technical success with partners: be accountable for the technical outcomes of our strategic pharma and biotech deployments, from first scoping conversation through production.
• Stay hands-on: review and contribute to prototypes, MCP integrations, agentic workflows, and Claude Code for Bio solutions; help the team get unblocked on the hardest technical problems.
• Build agent-ready scientific infrastructure: guide the team in creating the deterministic tools, connectors/harnesses, and evaluations that make messy biological data and workflows reliably accessible to Claude — in partnership with scientists and research institutions.
• Translate the field into the roadmap: partner cross functionally to turn what you learn from deployments into improvements in Anthropic's life sciences products and models.
• Set the standard for responsible deployment: work alongside our safety teams to enable beneficial scientific work while guarding against misuse in a dual-use domain.
• Build for the frontier: use deep knowledge of frontier model intelligence coupled to your work in R&D and research to rapidly progress toward solutions to meaningful problems in life sciences.

Requirements

• Have led or technically mentored software/ML engineers, ideally in a forward-deployed, solutions, or customer-facing engineering setting.
• Have a background in pharma, biotech, computational biology, bioinformatics, or clinical/regulatory affairs.
• Have a strong hands-on engineering background and are comfortable reading and writing production code, not just managing those who do.
• Have delivered technical work directly with external customers or partners, and can communicate credibly with both technical experts and executives.
• Have built on top of large language models or agents.
• Are energized by an unfamiliar technical domain and have a track record of going deep fast.
• Hold a high bar for reliability and reproducibility, and understand why a plausible-looking answer that's subtly wrong can be worse than no answer in scientific work.
• Have built tooling, data infrastructure, evals, or agent harnesses that turn messy real-world data into something usable and trustworthy — especially welcome if in a scientific or research setting.
• Care deeply about the safe and beneficial deployment of AI, especially in sensitive domains.

Nice-to-Haves

• Experience deploying LLM or agent systems in regulated or enterprise environments.
• Experience building MCP servers, developer tooling, or scientific computing pipelines.
• Experience scaling a customer-facing technical team through a period of rapid growth.

Compensation & Benefits

• Annual Salary: $320,000–$405,000 USD
• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
• Visa sponsorship available.